Improved detection of Clostridium difficile and a new method to type highly lethal hospital-acquired infections due to C. difficile

Said, M 2011, Improved detection of Clostridium difficile and a new method to type highly lethal hospital-acquired infections due to C. difficile, Masters by Research, Applied Sciences, RMIT University.


Document type: Thesis
Collection: Theses

Attached Files
Name Description MIMEType Size
Said.pdf Thesis application/pdf 17.43MB
Title Improved detection of Clostridium difficile and a new method to type highly lethal hospital-acquired infections due to C. difficile
Author(s) Said, M
Year 2011
Abstract The incidence of hypervirulent epidemic Clostridium difficile has increased around the world and now in Australia. Assays that are capable of rapidly identifying these strains would enable earlier diagnosis and timely infection control response. The aims of the first part of the study were to validate and develop a molecular technique for the rapid diagnosis of toxigenic C. difficile from faecal samples using a multiplex real-time PCR assay and the development of a real-time PCR assay to identify strains carrying the frame shift mutation in the tcdC gene characteristic of hypervirulent strains. DNA extracted from stool samples was tested in real-time PCR. A real-time PCR targeting the tcdC frameshift mutation at position 117 (Δ117PCR) was investigated for identifying ribotype 027 C. difficile directly from stool samples. Using CTA as the “gold standard”, the sensitivity and specificity for the multiplex real- time PCR were 97% and 51.4% respectively. Comparing conventional PCR results of toxin genes from isolate DNA, the sensitivity and specificity for the multiplex real- time PCR were 100% and 80% respectively, and comparing conventional PCR results of toxin genes from stool samples, the sensitivity and specificity for the multiplex real- time PCR were 100% and 71.4% respectively.

In the second part of this study we investigated a high resolution melt analysis (HRM) of PCR ribotyping products. Ribotyping was performed using the published primers of Bidet et al. (1999) and band patterns were analysed using GelCompar II. The same primers were used to perform real-time PCR. The PCR normalised melt curves were imported into ScreenClust software (QIAGEN) to generate principal component analysis graphs depicting clustered relationships of strains. Ribotyping produced clear PCR bands for 88/98 isolates tested. A dendrogram generated by GelCompar II showed a diversity of ribotype patterns amongst these 88 clinical isolates with 18 groups identified with 70% homology. Three of the four control 027 ribotype isolates showed 100% homology (R20291, KI and CD196). The fourth showed 82% homology with the other 027 control strains. One clinical isolate showed 98% homology with the control 027 strains and was shown to produce the toxins tcdA, tcdB, cdtA and cdtB and contained the frameshift mutation characteristic of epidemic 027 strains. ScreenClust analysis of the same 88 HRM results showed clustering of isolates, with 027 strains identifiable as a unique cluster. HRM analysis correctly identified the control 027 stains and the clinical isolate shown also to be 027.

The real-time PCR assay of toxin genes in stool was performed in 4 hours and thus can serve as a rapid assay for patients suspected of having CDI. A real-time PCR targeting the tcdC frameshift mutation at position 117 successfully identified a ribotype 027 strain in our patient population. HRM analysis of the real-time PCR products of the intergenic (16S-23S rDNA) spacer region has enabled the identification of ribotype 027 hypervirulent strains. It has enabled the identification to occur within 2 – 3 hours of colony isolation and thus is a valuable aid in the timely identification of these strains so that infection control can be rapidly implemented.
Degree Masters by Research
Institution RMIT University
School, Department or Centre Applied Sciences
Keyword(s) Clostridium difficile
ribotype 027 hypervirulent strains
HRM and ScreenClust
Versions
Version Filter Type
Access Statistics: 212 Abstract Views, 393 File Downloads  -  Detailed Statistics
Created: Fri, 21 Sep 2012, 14:57:26 EST by Keely Chapman
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us